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Experiments in AML cell lines where we assess proteomics of single and double drug treatments.

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P3: AML Drug Combination Analysis

This project provides the basic analysis and tools for carrying out end-to-end proteomic analysis for data generated at PNNL. This repository will serve as a resource upon which we can build additional tools in a reusable fashion. Ideally we will include scripts and libraries that can be used as building blocks for future analysis. We will use these scripts to specifically analyze drug combination data.

Overview

This section describes what you need to know to get started using this code base.

To use this pipeline

This repository is only the basic structure of the tools needed, not the end-to-end analysis. Here are the steps you'll need to use this:

  1. Read up on the tools. GitHub requires some basic protocols such as pull requests and commits, you should try to get a basic understanding. I found this tutorial that can serve as a starting point. Synapse also has a bit of learning curve. To understand what Synapse is and isn't, check out this document.
  2. Get RStudio. Basic R is essential, but RStudio will make your life a lot easier, I promise!
  3. Install the synapse python client, create a .synapseConfig file in your home directory.
  4. Click on the Use this template button above. This will allow you to create your own repository. Then you can follow the steps below.
  5. Create a new Synapse Project to store data for this project, or request access to an existing one.

To contribute to this pipeline

Have something that we forgot? Great! Check out the CONTRIBUTING.md document. We welcome all additional tool and methods. Then you can create a pull request and merge your code in.

Data description

This specific instantiation of P3 focuses on the drug combination data in AML cell lines. Specifically we have two types of cell lines with three different drugs, depicted in here (add screenshot here).

Data type Cell Line Conditions Link
Proteomics HL60 syn25813233
Phosphoproteomics HL60 syn25813243
Proteomics uncorrected HL60 syn25813236
Phosphoproteomics uncorrected HL60 syn25813252
Proteomics Molm14 syn25813133
Phosphoproteomics Molm14 syn25813172
Proteomics uncorrected Molm14 syn25813139
Phosphoproteomics uncorrected Molm14 syn25813182

Using these data from the various time points and drug treatments we want to evaluate changes that occur.

Pipeline description

This pipeline links together a series of data and code repositories to ensure that any data is saved for future use. Furthermore we hope to be able to reproduce the analysis for future projects. A brief overview of each tool is described here. arch

Proteomics and phosphoproteomics processing

This processing relies on a series of customized R scripts that are in the following directories:

  • global: global proteomics analysis documentation is here
  • phospo: phosphoproteomics analysis documentation is here Once this analysis is complete, the data should be stored on Synapse

Synapse processing

Synapse is used for:

  • data storage: data is backed up for free
  • data processing: UUIDs and permission modifications allow for easy analysis
  • data release: data can be moved to the PDC or shared

You will need to acquire a synapse username to access synapse, and become a certified user to add data, but after that you will be set with future projects. We created a test site at http://synapse.org/p3.

Functional analysis

There are typically a few steps we do for functional analysis. They are described in the functional analysis directory for now.

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Experiments in AML cell lines where we assess proteomics of single and double drug treatments.

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